The myth of standardized workflow in primary care

Implementing an advanced team-based care model in a federally qualified health center (FQHC): Assessing implementation facilitators and challenges

OBJECTIVE

The objective of this paper is to assess implementation facilitators and challenges for advanced team-based care (aTBC) in a federally qualified health center (FQHC). In aTBC, care team coordinators room patients, perform vitals and agenda setting during patient intake, and remain present alongside providers during patient visits.

METHODS

The authors conducted a qualitative post-hoc analysis of the aTBC implementation using data from several sources. They used content analysis to code items as facilitators or challenges and thematic analysis to group those into larger themes. Finally, they applied a priori codes from the revised consolidated framework for implementation research (CFIR) to organize the facilitators and barriers into subdomains.

RESULTS

The existing evidence-base around aTBC, the FQHC's ability to pilot and adapt it, and strong implementation leads were key facilitating factors. Challenges included an external shock (i.e., the COVID-19 pandemic), aTBC complexity, and uncertainty about whether success required implementation of the full model versus easier-to-integrate smaller components.

CONCLUSIONS

FQHCs that wish to implement aTBC models need strong champions and internal structures for piloting, adapting, and disseminating interventions. FQHC leaders must think strategically about how to build support and demonstrate success to improve an FQHC's chances of expanding and sustaining aTBC.

Navigating the doctor-patient-AI relationship - a mixed-methods study of physician attitudes toward artificial intelligence in primary care

BACKGROUND

Artificial intelligence (AI) is a rapidly advancing field that is beginning to enter the practice of medicine. Primary care is a cornerstone of medicine and deals with challenges such as physician shortage and burnout which impact patient care. AI and its application via digital health is increasingly presented as a possible solution. However, there is a scarcity of research focusing on primary care physician (PCP) attitudes toward AI. This study examines PCP views on AI in primary care. We explore its potential impact on topics pertinent to primary care such as the doctor-patient relationship and clinical workflow. By doing so, we aim to inform primary care stakeholders to encourage successful, equitable uptake of future AI tools. Our study is the first to our knowledge to explore PCP attitudes using specific primary care AI use cases rather than discussing AI in medicine in general terms.

METHODS

From June to August 2023, we conducted a survey among 47 primary care physicians affiliated with a large academic health system in Southern California. The survey quantified attitudes toward AI in general as well as concerning two specific AI use cases. Additionally, we conducted interviews with 15 survey respondents.

RESULTS

Our findings suggest that PCPs have largely positive views of AI. However, attitudes often hinged on the context of adoption. While some concerns reported by PCPs regarding AI in primary care focused on technology (accuracy, safety, bias), many focused on people-and-process factors (workflow, equity, reimbursement, doctor-patient relationship).

CONCLUSION

Our study offers nuanced insights into PCP attitudes towards AI in primary care and highlights the need for primary care stakeholder alignment on key issues raised by PCPs. AI initiatives that fail to address both the technological and people-and-process concerns raised by PCPs may struggle to make an impact.

Determinants for scalable adoption of autonomous AI in the detection of diabetic eye disease in diverse practice types: key best practices learned through collection of real-world data

Autonomous Artificial Intelligence (AI) has the potential to reduce disparities, improve quality of care, and reduce cost by improving access to specialty diagnoses at the point-of-care. Diabetes and related complications represent a significant source of health disparities. Vision loss is a complication of diabetes, and there is extensive evidence supporting annual eye exams for prevention. Prior to the use of autonomous AI, store-and-forward imaging approaches using remote reading centers (asynchronous telemedicine) attempted to increase diabetes related eye exams with limited success. In 2018, after rigorous clinical validation, the first fully autonomous AI system [LumineticsCore™ (formerly IDx-DR), Digital Diagnostics Inc., Coralville, IA, United States] received U.S. Food and Drug Administration (FDA) De Novo authorization. The system diagnoses diabetic retinopathy (including macular edema) without specialist physician overread at the point-of-care. In addition to regulatory clearance, reimbursement, and quality measure updates, successful adoption requires local optimization of the clinical workflow. The general challenges of frontline care clinical workflow have been well documented in the literature. Because healthcare AI is so new, there remains a gap in the literature about challenges and opportunities to embed diagnostic AI into the clinical workflow. The goal of this review is to identify common workflow themes leading to successful adoption, measured as attainment number of exams per month using the autonomous AI system against targets set for each health center. We characterized the workflow in four different US health centers over a 12-month period. Health centers were geographically dispersed across the Midwest, Southwest, Northeast, and West Coast and varied distinctly in terms of size, staffing, resources, financing and demographics of patient populations. After 1 year, the aggregated number of diabetes-related exams per month increased from 89 after the first month of initial deployment to 174 across all sites. Across the diverse practice types, three primary determinants underscored sustainable adoption: (1) Inclusion of Executive and Clinical Champions; (2) Underlining Health Center Resources; and (3) Clinical workflows that contemplate patient identification (pre-visit), LumineticsCore Exam Capture and Provider Consult (patient visit), and Timely Referral Triage (post-visit). In addition to regulatory clearance, reimbursement and quality measures, our review shows that addressing the core determinants for workflow optimization is an essential part of large-scale adoption of innovation. These best practices can be generalizable to other autonomous AI systems in front-line care settings, thereby increasing patient access, improving quality of care, and addressing health disparities.

Small Changes in Patient Arrival and Consultation Times Have Large Effects on Patients' Waiting Times: Simulation Analyses for Primary Care

(1) Background: Workflows are a daily challenge in general practices. The desired smooth work processes and patient flows are not easy to achieve. This study uses an operational research approach to illustrate the general effects of patient arrival and consultation times on waiting times. (2) Methods: Stochastic simulations were used to model complex daily workflows of general practice. Following classical queuing models, patient arrivals, queuing discipline, and physician consultation times are three key factors influencing work processes. (3) Results: In the first scenario, with patients arriving every 7.6 min and random consultation times, the individual patients' maximum waiting time increased to more than 200 min. The second scenario with random patient arrivals and random consultation times increased the average waiting time by up to 30 min compared to patients arriving on schedule. A busy morning session based on the second scenario was investigated to compare two alternative intervention strategies to reduce subsequent waiting times. Both could reduce waiting times by a multiple for each minute of reduced consultation time. (4) Conclusions: Aiming to improve family physicians' awareness of strategies for improving workflows, this simulation study illustrates the effects of strategies that address consultation times and patient arrivals.

When is caring sharing? Primary care provider interdependence and continuity of care

ABSTRACT

Efforts to improve access to high-quality, efficient primary care have highlighted the need for team-based care. Most primary care teams are designed to maintain continuity of care between patients and primary care providers (PCPs), because continuity of care can improve some patient outcomes. However, PCPs are interdependent because they care for, or share, patients. PCP interdependence, and its association with continuity of care, is not well described. This study describes a measure of PCP interdependence. We also evaluate the association between patient and panel characteristics, including PCP interdependence. Our results found that the extent of interdependence between PCPs in the same clinic varies widely. A range of patient and panel characteristics affect continuity of care, including patient complexity and PCP interdependence. These results suggest that continuity of care for complex patients is sensitive to panel characteristics, including PCP interdependence and panel size. This information can be used by primary care organizations for evidence-based team design.

Teaming up in primary care: Membership boundaries, interdependence, and coordination

OBJECTIVE

Increased demand for quality primary care and value-based payment has prompted interest in implementing primary care teams. Evidence-based recommendations for implementing teams will be critical to successful PA participation. This study sought to describe how primary care providers (PCPs) define team membership boundaries and coordinate tasks.

METHODS

This mixed-methods study included 28 PCPs from a primary care network. We analyzed survey data using descriptive statistics and interview data using content analysis.

RESULTS

Ninety-six percent of PCPs reported team membership. Team models fell into one of five categories. The predominant coordination mechanism differed by whether coordination was required in a visit or between visits.

CONCLUSIONS

Team-based primary care is a strategy for improving access to quality primary care. Most PCPs define team membership based on within-visit task interdependencies. Our findings suggest that team-based interventions can focus on clarifying team membership, increasing interaction between clinicians, and enhancing the electronic health record to facilitate between-visit coordination.

User-centered design of a scalable, electronic health record-integrated remote symptom monitoring intervention for patients with asthma and providers in primary care

OBJECTIVE

To determine user and electronic health records (EHR) integration requirements for a scalable remote symptom monitoring intervention for asthma patients and their providers.

METHODS

Guided by the Non-Adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework, we conducted a user-centered design process involving English- and Spanish-speaking patients and providers affiliated with an academic medical center. We conducted a secondary analysis of interview transcripts from our prior study, new design sessions with patients and primary care providers (PCPs), and a survey of PCPs. We determined EHR integration requirements as part of the asthma app design and development process.

RESULTS

Analysis of 26 transcripts (21 patients, 5 providers) from the prior study, 21 new design sessions (15 patients, 6 providers), and survey responses from 55 PCPs (71% of 78) identified requirements. Patient-facing requirements included: 1- or 5-item symptom questionnaires each week, depending on asthma control; option to request a callback; ability to enter notes, triggers, and peak flows; and tips pushed via the app prior to a clinic visit. PCP-facing requirements included a clinician-facing dashboard accessible from the EHR and an EHR inbox message preceding the visit. PCP preferences diverged regarding graphical presentations of patient-reported outcomes (PROs). Nurse-facing requirements included callback requests sent as an EHR inbox message. Requirements were consistent for English- and Spanish-speaking patients. EHR integration required use of custom application programming interfaces (APIs).

CONCLUSION

Using the NASSS framework to guide our user-centered design process, we identified patient and provider requirements for scaling an EHR-integrated remote symptom monitoring intervention in primary care. These requirements met the needs of patients and providers. Additional standards for PRO displays and EHR inbox APIs are needed to facilitate spread.

Remembering Ben-Tzion Karsh's scholarship, impact, and legacy

Dr. Ben-Tzion (Bentzi) Karsh was a mentor, collaborator, colleague, and friend who profoundly impacted the fields of human factors and ergonomics (HFE), medical informatics, patient safety, and primary care, among others. In this paper we honor his contributions by reflecting on his scholarship, impact, and legacy in three ways: first, through an updated simplified bibliometric analysis in 2020, highlighting the breadth of his scholarly impact from the perspective of the number and types of communities and collaborators with which and whom he engaged; second, through targeted reflections on the history and impact of Dr. Karsh's most cited works, commenting on the particular ways they impacted our academic community; and lastly, through quotes from collaborators and mentees, illustrating Dr. Karsh's long-lasting impact on his contemporaries and students.

Using a Clinical Workflow Analysis to Enhance eHealth Implementation Planning: Tutorial and Case Study

eHealth apps often fail to improve clinical outcomes due to poor integration with clinical workflow-the sequence and personnel needed to undertake a series of tasks for clinical care. Our central thesis is that eHealth interventions will be more effective if the clinical workflow is studied and taken into consideration for intervention implementation. This paper aims to provide an introductory tutorial on when and how to use a clinical workflow analysis to guide the implementation of eHealth interventions. The tutorial includes a step-by-step guide to conducting a clinical workflow analysis in planning for eHealth implementation. We began with a description of why a clinical workflow analysis is best completed before the implementation of eHealth interventions. Next, we described 4 steps needed to perform the clinical workflow analysis: the identification of discrete workflow components, workflow assessment, triangulation, and the stakeholder proposal of intervention implementation. Finally, we presented a case study of a clinical workflow analysis, which was conducted during patient visits of patients aged 11 or 12 years from 4 diverse pediatric or family medicine clinics to plan the implementation of a tablet-based app for adolescent vaccination. Investigators planning the implementation of new eHealth interventions in health care settings can use the presented steps to assess clinical workflow, thereby maximizing the match of their intervention with the clinical workflow. Conducting a prospective workflow study allows for evidence-based planning, identifying potential pitfalls, and increasing stakeholder buy-in and engagement. This tutorial should aid investigators in increasing the successful implementation of eHealth interventions.

Time-motion examination of electronic health record utilization and clinician workflows indicate frequent task switching and documentation burden

Clinical documentation burden has been broadly acknowledged, yet few interprofessional measures of burden exist. Using interprofessional time-motion study (TMS) data, we evaluated clinical workflows with a focus on electronic health record (EHR) utilization and fragmentation among 47 clinicians: 34 advanced practice providers (APPs) and 13 registered nurses (RNs) from: an acute care unit (n=15 observations [obs]), intensive care unit (nobs=14), ambulatory clinic (nobs=3), and emergency department (nobs=15). We examined workflow fragmentation, task-switch type, and task involvement. In our study, clinicians on average exhibited 1.4±0.6 switches per minute in their workflow. Eighty-four (19.6%) of the 429 task-switch types presented in the data accounted for 80.1% of all switches. Among those, data viewing- and data entry-related tasks were involved in 48.2% of all switches, indicating documentation burden may play a critical role in workflow disruptions. Therefore, interruption rate evaluated through task switches may serve as a proxy for measuring burden.

Patient monitoring as a predictor of blood culture results in a tertiary neonatal intensive care unit

We present a mesoergonomic approach to the early detection of neonatal sepsis, analyzing clinical data for 4999 patients from a neo-natal intensive care unit to predict positive culture results. The Apgar score at birth predicted positive results. For neonates with poor and intermediate Apgar scores, culture results for monitored infants were more likely to be positive than those for unmonitored infants. Thus, the medical staff tended to monitor infants who eventually had a greater chance for positive test results. A cost-effectiveness analysis indicated that for infants with high Apgar scores, the physician should decide whether to obtain a blood culture, based on the patient's characteristics. For infants with lower Apgar scores, it may be advisable to obtain a blood culture whenever one decides to monitor a neonate. The study demonstrates that staff decisions regarding a patient can serve as input for further clinical decision-making.

The Relationships Between Patient Experience and Quality and Utilization of Primary Care Services

We lack knowledge on how patient-reported experience relates to both quality of care services and visit attendance in the primary care setting. Therefore, in a cross-sectional analysis of 8355 primary care patients from 22 primary care practices, we examined the associations between visit-triggered patient-reported experience measures and both (1) quality of care measures and (2) number of missed primary care appointment (no shows). Our independent variables included both overall patient experience and its subdomains. Our outcomes included the following measures: smoking cessation discussion, diabetes eye examination referral, mammography, colonoscopy screening, current smoking status (nonsmoker vs smoker), diabetes control Hemoglobin A1c (HbA1c [<8]), blood pressure control, cholesterol control Low Density Lipoprotein (LDL) among patients with diabetes (LDL < 100), and visit no shows 2 and 5 years after the index visit that triggered the completed patient-experience survey. We found that patient experience, while an important stand-alone metric of care quality, may not relate to clinical outcomes or process measures in the outpatient setting. However, patient-reported experiences with their primary care provider appear to influence their future visit attendance.

A Markov chain model for analysis of physician workflow in primary care clinics

This paper studies physician workflow management in primary care clinics using terminating Markov chain models. The physician workload is characterized by face-to-face encounters with patients and documentation of electronic health record (EHR) data. Three workflow management policies are considered: preemptive priority (stop ongoing documentation tasks if a new patient arrives); non-preemptive priority (finish ongoing documentation even if a new patient arrives); and batch documentation (start and finish documentation when the desired number of tasks is reached). Analytical formulas are derived to quantify the performance measures of three management policies, such as physician's daily working time, patient's waiting time, and documentation waiting time. A comparison of the results under three policies is carried out. Finally, a case study in a primary care clinic is carried out to illustrate model applicability. Such a work provides a quantitative tool for primary care physicians to design and manage their workflow to improve care quality.

Tailoring EHRs for Specific Working Environments Improves Work Well-Being of Physicians

Electronic health records (EHRs) have an impact on physicians’ well-being and stress levels. We studied physicians’ experiences with EHRs and their experienced time pressure and self-rated stress by an electronic questionnaire sent to Finnish physicians aged under 65 in 2017. Our sample was 2980 physicians working in the public sector, health care centers (35.5%) or hospitals (64.5%). Experienced technical problems were positively associated with experienced time pressure, whereas user-friendliness of the EHRs was negatively associated with experienced time pressure. Low perceived support for internal cooperation was associated with high levels of time pressure in hospitals. Those experiencing high levels of technical problems were 1.3 times more likely to experience stress compared to those experiencing low levels of technical problems. Better user-friendliness of the EHRs was associated with lower levels of self-rated stress. In both working environments but more strongly in primary health care, technical problems were associated with self-rated stress. Technical problems and user-friendliness of EHRs are the main factors associated with time pressure and self-rated stress. Health care environments differ in the nature of workflow having different demands on the EHRs. Developing EHR systems should consider the special needs of different environments and workflows, enabling better work well-being amongst physicians.

Relationship between number of health problems addressed during a primary care patient visit and clinician workload

INTRODUCTION

Primary care is complex due to multiple health problems being addressed in each patient visit. Little is known about the effect of the number of problems per encounter (NPPE) on the resulting clinician workload (CWL), as measured using the National Aeronautics and Space Administration Task Load Index (NASA-TLX).

METHODS

We evaluated the relationship between NPPE and CWL across 608 adult patient visits, conducted by 31 clinicians, using hierarchical linear regression. Clinicians were interviewed about outlier visits to identify reasons for higher or lower than expected CWL.

RESULTS

Mean NPPE was 3.30 ± 2.0 (sd) and CWL was 47.6 ± 18.4 from a maximum of 100. Mental demand, time demand and effort accounted for 71.5% of CWL. After adjustment for confounders, each additional problem increased CWL by 3.9 points (P < 0.001). Patient, problem, environmental and patient-physician relationship factors were qualitatively identified from interviews as moderators of this effect.

CONCLUSION

CWL is positively related to NPPE. Several modifiable factors may enhance or mitigate this effect. Our findings have implications for using a Human Factors (HF) approach to managing CWL.

Impacts of Operational Failures on Primary Care Physicians' Work: A Critical Interpretive Synthesis of the Literature

PURPOSE

Operational failures are system-level errors in the supply of information, equipment, and materials to health care personnel. We aimed to review and synthesize the research literature to determine how operational failures in primary care affect the work of primary care physicians.

METHODS

We conducted a critical interpretive synthesis. We searched 7 databases for papers published in English from database inception until October 2017 for primary research of any design that addressed problems interfering with primary care physicians' work. All potentially eligible titles/abstracts were screened by 1 reviewer; 30% were subject to second screening. We conducted an iterative critique, analysis, and synthesis of included studies.

RESULTS

Our search retrieved 8,544 unique citations. Though no paper explicitly referred to "operational failures," we identified 95 papers that conformed to our general definition. The included studies show a gap between what physicians perceived they should be doing and what they were doing, which was strongly linked to operational failures-including those relating to technology, information, and coordination-over which physicians often had limited control. Operational failures actively configured physicians' work by requiring significant compensatory labor to deliver the goals of care. This labor was typically unaccounted for in scheduling or reward systems and had adverse consequences for physician and patient experience.

CONCLUSIONS

Primary care physicians' efforts to compensate for suboptimal work systems are often concealed, risking an incomplete picture of the work they do and problems they routinely face. Future research must identify which operational failures are highest impact and tractable to improvement.

The Impact of Electronic Health Records on the Duration of Patients' Visits: Time and Motion Study

BACKGROUND

Despite the many benefits of electronic health records (EHRs), studies have reported that EHR implementation could create unintended changes in the workflow if not studied and designed properly. These changes may impact the time patients spend on the various steps of their visits, such as the time spent in the waiting area and the time spent with a physician. The amount of time patients spend in the waiting area before consultation is often a strong predictor of patient satisfaction, willingness to come back for a return visit, and overall experience. The majority of prior studies that examined the impact of EHR systems on time focused on single aspects of patient visits or user (physicians or nurses) activities. The impact of EHR use on patients' time spent during the different aspects of the visit is rarely investigated.

OBJECTIVE

This study aimed to evaluate the impact of EHR systems on the amount of time spent by patients on different tasks during their visit to primary health care (PHC) centers.

METHODS

A time and motion observational study was conducted at 4 PHC centers. The PHC centers were selected using stratified randomized sampling. Of the 4 PHC centers, 2 used an EHR system and 2 used a paper-based system. Each group had 1 center in a metropolitan area and another in a rural area. In addition, a longitudinal observation was conducted at one of the PHC centers after 1 year and again after 2 years of implementation. The analysis included descriptive statistics and group comparisons.

RESULTS

The results showed no significant difference in the amount of time spent by patients in the reception area (P=.26), in the waiting area (P=.57), consultation time (P=.08), and at the pharmacy (P=.28) between the EHR and paper based groups. However, there was a significant difference (P<.001) in the amount of time spent on all tasks between the PHC centers located in metropolitan and rural areas. The longitudinal observation also showed reduction in the registration time (from 5.5 [SD 3.5] min to 0.9 [SD 0.5] min), which could be attributed to the introduction of a Web-based booking system.

CONCLUSIONS

The variation in the time patients spend at PHC centers is more likely to be attributed to the facility location than EHR use. The changes in the introduction of new tools and functions, however, such as the Web-based booking system, can impact the duration of patients' visits.

CM-SHARE: Development, Integration, and Adoption of an Electronic Health Record-Linked Digital Health Solution to Support Care for Diabetes in Primary Care

IN BRIEF Chronic conditions such as diabetes are largely managed by primary care providers (PCPs), with significant patient self-management. This article describes the development, pilot testing, and fine-tuning of a Web-based digital health solution to help PCPs manage patients with cardiometabolic diseases during routine office encounters. It shows that such products can be successfully integrated into primary care settings when they address important unmet needs and are developed with input from end-users.

Visualising clinical work in the emergency department: Understanding interleaved patient management

We present a unique data visualisation approach, called workflow time charts, to illustrate the sequential and multi-dimensional nature of work in emergency departments. Using 40 h of data from direct observations of emergency physicians, we applied the charts to visualise patient-stratified physicians' work as a continuous temporal process, including distinguishing tasks of different types and representing external prompts (similar to interruptions) and multitasking performance. The charts showed frequent changes in the nature of observed activities, with interleaved multitasking a constant feature and external prompts often clustered in time. Evidence of seniority-related differences in work were apparent with consultants switching between more concurrent patients and receiving more frequent clinical prompts than junior physicians, illustrating their overseeing and advice-giving role. The ubiquity of interleaved multitasking suggests a need to focus on developing individual strategies to support frequent cognitive switching. Work that appears fragmented at physician level may form part of a flexible and robust system, rather than an error-prone set of isolated individual behaviours.

Live Usability Testing of Two Complex Clinical Decision Support Tools: Observational Study

BACKGROUND

Potential of the electronic health records (EHR) and clinical decision support (CDS) systems to improve the practice of medicine has been tempered by poor design and the resulting burden they place on providers. CDS is rarely tested in the real clinical environment. As a result, many tools are hard to use, placing strain on providers and resulting in low adoption rates. The existing CDS usability literature relies primarily on expert opinion and provider feedback via survey. This is the first study to evaluate CDS usability and the provider-computer-patient interaction with complex CDS in the real clinical environment.

OBJECTIVE

This study aimed to further understand the barriers and facilitators of meaningful CDS usage within a real clinical context.

METHODS

This qualitative observational study was conducted with 3 primary care providers during 6 patient care sessions. In patients with the chief complaint of sore throat, a CDS tool built with the Centor Score was used to stratify the risk of group A Streptococcus pharyngitis. In patients with a chief complaint of cough or upper respiratory tract infection, a CDS tool built with the Heckerling Rule was used to stratify the risk of pneumonia. During usability testing, all human-computer interactions, including audio and continuous screen capture, were recorded using the Camtasia software. Participants' comments and interactions with the tool during clinical sessions and participant comments during a postsession brief interview were placed into coding categories and analyzed for generalizable themes.

RESULTS

In the 6 encounters observed, primary care providers toggled between addressing either the computer or the patient during the visit. Minimal time was spent listening to the patient without engaging the EHR. Participants mostly used the CDS tool with the patient, asking questions to populate the calculator and discussing the results of the risk assessment; they reported the ability to do this as the major benefit of the tool. All providers were interrupted during their use of the CDS tool by the need to refer to other sections of the chart. In half of the visits, patients' clinical symptoms challenged the applicability of the tool to calculate the risk of bacterial infection. Primary care providers rarely used the incorporated incentives for CDS usage, including progress notes and patient instructions.

CONCLUSIONS

Live usability testing of these CDS tools generated insights about their role in the patient-provider interaction. CDS may contribute to the interaction by being simultaneously viewed by the provider and patient. CDS can improve usability and lessen the strain it places on providers by being short, flexible, and customizable to unique provider workflow. A useful component of CDS is being as widely applicable as possible and ensuring that its functions represent the fastest way to perform a particular task.

How often do both core competencies of shared decision making occur in family medicine teaching clinics?

OBJECTIVE

To assess how often risk communication and values clarification occur in routine family medicine practice and to explore factors associated with their occurrence.

DESIGN

Qualitative and quantitative cross-sectional study.

SETTING

Five university-affiliated family medicine teaching clinics across Quebec.

PARTICIPANTS

Seventy-one health professionals (55% physicians, 35% residents, 10% nurses or dietitians) and 238 patients (76% women; age range 16 to 82 years old).

MAIN OUTCOME MEASURES

The presence or absence of risk communication and values clarification during visits in which decisions were made was determined. Factors associated with the primary outcome (both competencies together) were identified. The OPTION5 (observing patient involvement in decision making) instrument was used to validate the dichotomous outcome.

RESULTS

The presence of risk communication and values clarification during visits was associated with OPTION5 scores (area under the curve of 0.80, 95% CI 0.75 to 0.86, P < .001). Both core competencies of shared decision making occurred in 150 of 238 (63%) visits (95% CI 54% to 70%). Such an occurrence was more likely when the visit included discussion about beginning something new, treatment options, or postponing a decision, as well as when health professionals preferred a collaborative decision-making style and when the visit included more decisions or was longer. Alone, risk communication occurred in 203 of 238 (85%) visits (95% CI 82% to 96%) and values clarification in 162 of 238 (68%) visits (95% CI 61% to 75%).

CONCLUSION

Health professionals in family medicine are making an effort to engage patients in shared decision making in routine daily practice, especially when there is time to do so. The greatest potential for improvement might lie in values clarification; that is, discussing what matters to patients and families.

Designing a medication timeline for patients and physicians

Objective

Most electronic health records display historical medication information only in a data table or clinician notes. We designed a medication timeline visualization intended to improve ease of use, speed, and accuracy in the ambulatory care of chronic disease.

Materials and Methods

We identified information needs for understanding a patient medication history, then applied human factors and interaction design principles to support that process. After research and analysis of existing medication lists and timelines to guide initial requirements, we hosted design workshops with multidisciplinary stakeholders to expand on our initial concepts. Subsequent core team meetings used an iterative user-centered design approach to refine our prototype. Finally, a small pilot evaluation of the design was conducted with practicing physicians.

Results

We propose an open-source online prototype that incorporates user feedback from initial design workshops, and broad multidisciplinary audience feedback. We describe the applicable design principles associated with each of the prototype's key features. A pilot evaluation of the design showed improved physician performance in 5 common medication-related tasks, compared to tabular presentation of the same information.

Discussion

There is industry interest in developing medication timelines based on the example prototype concepts. An open, standards-based technology platform could enable developers to create a medication timeline that could be deployable across any compatible health IT application.

Conclusion

The design goal was to improve physician understanding of a patient's complex medication history, using a medication timeline visualization. Such a design could reduce temporal and cognitive load on physicians for improved and safer care.

Medical consultation, time and duration

This essay is a reflection of the time and duration of the medical consultation, seen as a social process that is determined by macro structures following the productive logic and the demands of modern time. The length of the medical discussion is heterogeneous worldwide; in contrast, what is standard is the perception of the professionals and the patients that the time for interaction is short. Such a perception pervades the doctor-patient relationship, perpetuating a cycle of dissatisfaction-tension-anxiety in these actors. Under the premise of the sociology of time and appealing to the ethical principles of medicine, we propose that the estimation in the length of a medical consultation must be considered. Time is indispensable for an adequate interaction to account for the needs of patients and professionals in a dignified manner since both have rights and obligations to be respected.

Test results management and distributed cognition in electronic health record-enabled primary care

Managing abnormal test results in primary care involves coordination across various settings. This study identifies how primary care teams manage test results in a large, computerized healthcare system in order to inform health information technology requirements for test results management and other distributed healthcare services. At five US Veterans Health Administration facilities, we interviewed 37 primary care team members, including 16 primary care providers, 12 registered nurses, and 9 licensed practical nurses. We performed content analysis using a distributed cognition approach, identifying patterns of information transmission across people and artifacts (e.g. electronic health records). Results illustrate challenges (e.g. information overload) as well as strategies used to overcome challenges. Various communication paths were used. Some team members served as intermediaries, processing information before relaying it. Artifacts were used as memory aids. Health information technology should address the risks of distributed work by supporting awareness of team and task status for reliable management of results.

Toward Timely Data for Cancer Research: Assessment and Reengineering of the Cancer Reporting Process

Background

Cancer registries systematically collect cancer-related data to support cancer surveillance activities. However, cancer data are often unavailable for months to years after diagnosis, limiting its utility.

Objective

The objective of this study was to identify the barriers to rapid cancer reporting and identify ways to shorten the turnaround time.

Methods

Certified cancer registrars reporting to the Indiana State Department of Health cancer registry participated in a semistructured interview. Registrars were asked to describe the reporting process, estimate the duration of each step, and identify any barriers that may impact the reporting speed. Qualitative data analysis was performed with the intent of generating recommendations for workflow redesign. The existing and redesigned workflows were simulated for comparison.

Results

Barriers to rapid reporting included access to medical records from multiple facilities and the waiting period from diagnosis to treatment. The redesigned workflow focused on facilitating data sharing between registrars and applying a more efficient queuing technique while registrars await the delivery of treatment. The simulation results demonstrated that our recommendations to reduce the waiting period and share information could potentially improve the average reporting speed by 87 days.

Conclusions

Knowing the time elapsing at each step within the reporting process helps in prioritizing the needs and estimating the impact of future interventions. Where some previous studies focused on automating some of the cancer reporting activities, we anticipate much shorter reporting by leveraging health information technologies to target this waiting period.

Considerations for developing chronic care system for traumatic brain injury based on comparisons of cancer survivorship and diabetes management care

Experts in traumatic brain injury (TBI) rehabilitation recently proposed the framing of TBI as a chronic disease rather than a discrete event. Within the framework of the Chronic Care Model (CCM), a systematic comparison of three diseases - cancer survivorship, diabetes management and TBI chronic care - was conducted regarding chronic needs and the management of those needs. In addition, comparisons of these conditions require comparative evaluations of disease management characteristics and the survivor concept. The analysis found diabetes is more established within the CCM, where care is integrated across specialists and primary care providers. No single comparison provides a full analogue for understanding the chronic care health delivery system for TBI, indicating the need for a separate model to address needs and resources for TBI survivors. The findings from this research can provide practitioners with a context to develop a robust continued care health system for TBI. Practitioner Summary: We examine development of a chronic care system for traumatic brain injury. We conducted a systematic comparison of Chronic Care Model elements of decision and information support. Development of capabilities using a benchmark of diabetes care, with additional insights from cancer care, provides insights for implementing TBI chronic care systems.

Tethered to the EHR: Primary Care Physician Workload Assessment Using EHR Event Log Data and Time-Motion Observations

PURPOSE

Primary care physicians spend nearly 2 hours on electronic health record (EHR) tasks per hour of direct patient care. Demand for non-face-to-face care, such as communication through a patient portal and administrative tasks, is increasing and contributing to burnout. The goal of this study was to assess time allocated by primary care physicians within the EHR as indicated by EHR user-event log data, both during clinic hours (defined as 8:00 am to 6:00 pm Monday through Friday) and outside clinic hours.

METHODS

We conducted a retrospective cohort study of 142 family medicine physicians in a single system in southern Wisconsin. All Epic (Epic Systems Corporation) EHR interactions were captured from "event logging" records over a 3-year period for both direct patient care and non-face-to-face activities, and were validated by direct observation. EHR events were assigned to 1 of 15 EHR task categories and allocated to either during or after clinic hours.

RESULTS

Clinicians spent 355 minutes (5.9 hours) of an 11.4-hour workday in the EHR per weekday per 1.0 clinical full-time equivalent: 269 minutes (4.5 hours) during clinic hours and 86 minutes (1.4 hours) after clinic hours. Clerical and administrative tasks including documentation, order entry, billing and coding, and system security accounted for nearly one-half of the total EHR time (157 minutes, 44.2%). Inbox management accounted for another 85 minutes (23.7%).

CONCLUSIONS

Primary care physicians spend more than one-half of their workday, nearly 6 hours, interacting with the EHR during and after clinic hours. EHR event logs can identify areas of EHR-related work that could be delegated, thus reducing workload, improving professional satisfaction, and decreasing burnout. Direct time-motion observations validated EHR-event log data as a reliable source of information regarding clinician time allocation.

Diabetic Eye Screening: Knowledge and Perspectives from Providers and Patients

PURPOSE OF REVIEW

Diabetic retinopathy remains the leading cause of blindness among working-age US adults even though timely screening and treatment prevent 90% of blindness. We summarize current knowledge and perspectives to better understand why diabetic eye screening rates remain low and future directions towards preventing blindness from diabetes.

RECENT FINDINGS

Significant advancements in the past 10 years include primary care and patient-oriented interventions as well as the use of teleophthalmology. In England, diabetic eye disease is no longer the leading cause of certifiable blindness following the implementation of a national teleophthalmology program for diabetic retinopathy. Multiple workflow and systems-level barriers affect providers. Patient barriers include a limited understanding of screening and lack of access to care. Interventions have been developed, but new barriers exist towards sustaining their impact. More research is needed to identify and implement the best practices to increase diabetic eye screening rates long-term.

"Think aloud" and "Near live" usability testing of two complex clinical decision support tools

OBJECTIVES

Low provider adoption continues to be a significant barrier to realizing the potential of clinical decision support. "Think Aloud" and "Near Live" usability testing were conducted on two clinical decision support tools. Each was composed of an alert, a clinical prediction rule which estimated risk of either group A Streptococcus pharyngitis or pneumonia and an automatic order set based on risk. The objective of this study was to further understanding of the facilitators of usability and to evaluate the types of additional information gained from proceeding to "Near Live" testing after completing "Think Aloud".

METHODS

This was a qualitative observational study conducted at a large academic health care system with 12 primary care providers. During "Think Aloud" testing, participants were provided with written clinical scenarios and asked to verbalize their thought process while interacting with the tool. During "Near Live" testing participants interacted with a mock patient. Morae usability software was used to record full screen capture and audio during every session. Participant comments were placed into coding categories and analyzed for generalizable themes. Themes were compared across usability methods.

RESULTS

"Think Aloud" and "Near Live" usability testing generated similar themes under the coding categories visibility, workflow, content, understand-ability and navigation. However, they generated significantly different themes under the coding categories usability, practical usefulness and medical usefulness. During both types of testing participants found the tool easier to use when important text was distinct in its appearance, alerts were passive and appropriately timed, content was up to date, language was clear and simple, and each component of the tool included obvious indicators of next steps. Participant comments reflected higher expectations for usability and usefulness during "Near Live" testing. For example, visit aids, such as automatically generated order sets, were felt to be less useful during "Near-Live" testing because they would not be all inclusive for the visit.

CONCLUSIONS

These complementary types of usability testing generated unique and generalizable insights. Feedback during "Think Aloud" testing primarily helped to improve the tools' ease of use. The additional feedback from "Near Live" testing, which mimics a real clinical encounter, was helpful for eliciting key barriers and facilitators to provider workflow and adoption.

The Challenges of Measuring, Improving, and Reporting Quality in Primary Care

We propose a new set of priorities for quality management in primary care, acknowledging that payers and regulators likely will continue to insist on reporting numerical quality metrics. Primary care practices have been described as complex adaptive systems. Traditional quality improvement processes applied to linear mechanical systems, such as isolated single-disease care, are inappropriate for nonlinear, complex adaptive systems, such as primary care, because of differences in care processes, outcome goals, and the validity of summative quality scorecards. Our priorities for primary care quality management include patient-centered reporting; quality goals not based on rigid targets; metrics that capture avoidance of excessive testing or treatment; attributes of primary care associated with better outcomes and lower costs; less emphasis on patient satisfaction scores; patient-centered outcomes, such as days of avoidable disability; and peer-led qualitative reviews of patterns of care, practice infrastructure, and intrapractice relationships.

Can Patient Record Summarization Support Quality Metric Abstraction?

We present a pre/post intervention study, where HARVEST, a general-purpose patient record summarization tool, was introduced to ten data abstraction specialists. The specialists are responsible for reviewing hundreds of patient charts each month and reporting disease-specific quality metrics to a variety of online registries and databases. We qualitatively and quantitatively investigated whether HARVEST improved the process of quality metric abstraction. Study instruments included pre/post questionnaires and log analyses of the specialists' actions in the electronic health record (EHR). The specialists reported favorable impressions of HARVEST and suggested that it was most useful when abstracting metrics from patients with long hospitalizations and for metrics that were not consistently captured in a structured manner in the EHR. A statistically significant reduction in time spent per chart before and after use of HARVEST was observed for 50% of the specialists and 90% of the specialists continue to use HARVEST after the study period.